Neural Network Models Of Cognition
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Neural Network Models of Cognition
This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity (LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural imaging and language. The volume also includes an integrated reference section and a comprehensive index.
Functional Models of Cognition
Author: A. Carsetti
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-11-11
Our ontology as well as our grammar are, as Quine affirms, ineliminable parts of our conceptual contribution to our theory of the world. It seems impossible to think of enti ties, individuals and events without specifying and constructing, in advance, a specific language that must be used in order to speak about these same entities. We really know only insofar as we regiment our system of the world in a consistent and adequate way. At the level of proper nouns and existence functions we have, for instance, a standard form of a regimented language whose complementary apparatus consists of predicates, variables, quantifiers and truth functions. If, for instance, the discoveries in the field of Quantum Mechanics should oblige us, in the future, to abandon the traditional logic of truth functions, the very notion of existence, as established until now, will be chal lenged. These considerations, as developed by Quine, introduce us to a conceptual perspective like the "internal realist" perspective advocated by Putnam whose principal aim is, for cer tain aspects, to link the philosophical approaches developed respectively by Quine and Wittgenstein. Actually, Putnam conservatively extends the approach to the problem of ref erence outlined by Quine: in his opinion, to talk of "facts" without specifying the language to be used is to talk of nothing.
Computational Modeling in Cognition
An accessible introduction to the principles of computational and mathematical modeling in psychology and cognitive science This practical and readable work provides students and researchers, who are new to cognitive modeling, with the background and core knowledge they need to interpret published reports, and develop and apply models of their own. The book is structured to help readers understand the logic of individual component techniques and their relationships to each other.